Data Scientist
Job Description
REQUIREMENTS
- 5+ years of experience in applied data science with models that reached production or client delivery
- Expertise in statistical modeling, including survey stats, causal inference, experimental design, and propensity/uplift modeling
- Working knowledge of Databricks and comfort working in Spark and Snowflake environments
- Strong proficiency in Python (pandas, scikit-learn, statsmodels) and SQL against large databases
- Quantitative degree in Statistics, Data Science, Economics, Computer Science, Math, or a similar field
Preferred
- Background in media or advertising
- Exposure to audience/identity or ad tech (DSP/SSP, DMP/CDP, clean rooms, identity graphs)
- Familiarity with privacy-preserving methods and GDPR/CCPA in data collaboration
RESPONSIBILITIES
- Build statistical and ML models to create, expand, and score audience segments from survey, panel, purchase, and media-exposure data
- Develop propensity and lookalike models that scale small seed audiences to addressable populations
- Lead data fusion work, combining deterministic and probabilistic sources into one representative consumer view while correcting for bias
- Ideate on product improvements by proposing new audiences, features, and methods
- Own audience measurement analytics, including reach, overlap, index strength, and incremental lift using A/B testing and causal inference
- Partner with ML Engineering to move models into reproducible, monitored production under privacy-by-design principles
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